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» Generation of Attributes for Learning Algorithms
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TIT
2008
76views more  TIT 2008»
13 years 9 months ago
Improved Risk Tail Bounds for On-Line Algorithms
We prove the strongest known bound for the risk of hypotheses selected from the ensemble generated by running a learning algorithm incrementally on the training data. Our result i...
Nicolò Cesa-Bianchi, Claudio Gentile
GLVLSI
2005
IEEE
133views VLSI» more  GLVLSI 2005»
14 years 2 months ago
Generating decision regions in analog measurement spaces
We develop a neural network that learns to separate the nominal from the faulty instances of a circuit in a measurement space. We demonstrate that the required separation boundari...
Haralampos-G. D. Stratigopoulos, Yiorgos Makris
CVPR
2011
IEEE
1473views Computer Vision» more  CVPR 2011»
13 years 5 months ago
Object Recognition with Hierarchical Kernel Descriptors
Kernel descriptors provide a unified way to generate rich visual feature sets by turning pixel attributes into patch-level features, and yield impressive results on many object rec...
Liefeng Bo, Kevin Lai, Xiaofeng Ren and Dieter Fox
ICPR
2008
IEEE
14 years 10 months ago
Semi-supervised learning on large complex simulations
Complex simulations can generate very large amounts of data stored disjointly across many local disks. Learning from this data can be problematic due to the difficulty of obtainin...
John Nicholas Korecki, Kevin W. Bowyer, Larry O. H...
ESWS
2007
Springer
14 years 3 months ago
Semantic Composition of Lecture Subparts for a Personalized e-Learning
Abstract. In this paper we propose an algorithm for personalized learning based on a user’s query and a repository of lecture subparts —i.e., learning objects— both are descr...
Naouel Karam, Serge Linckels, Christoph Meinel